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UMHexagonS搜索过程
通过相邻块的预测得到mvp后，会以mvp为基础搜索最佳的匹配块，UMHexagonS就是h.264中用的一种搜索算法。
UMHexagonS是一种整像素搜索算法，也就是搜索过程中，参考图像一直都是原来的重构图像，并没有使用经过插值的图像进行搜索。
首先UMHexagonS会根据相关信息去得到比较有可能的mv，（然后用小菱形搜索到该区域去搜索该区域中的最佳mv，这种情况会在下面注明）
由于UMHexagonS是一种整像素搜索算法，所以会存在对分数的mv取整的情况，此时取整是指把mv对齐到某个像素上，消去分数部分
1.mvp取整后得到的mv（然后采用小菱形搜索）
2.原点，mv为0，即当前块的位置（然后采用小菱形搜索）
3.上层块mv，如果当前块为8x8，那么覆盖当前块的16x8块就是其上层块
运动搜索中，分块模式有7种
模式4的上层模式为2，模式7的上层模式为4
4.共同位置块mv，取上一参考图像与当前块相同位置的块的mv,然后取整
5.共同位置参考mv通过参考图像距离计算后得到的mv，然后取整
6.最后还采用一次小菱形搜索，主要为了对上面3、4、5预测后得到的最佳mv再采用一次小菱形搜索以得到该区域内最佳mv
小菱形搜索就是把mv的x,y分别+1，-1后得到的新mv，然后各自对比得到其中最优的mv
在做完上方的整像素mv预测后，需要计算该mv的匹配满意程度，以跳转做不同的后续搜索处理，该过程叫Early Termination。
Early Termination由于涉及到数学上的分析，所以会在后面的章节再细述。
Early Termination有两个个跳转出口，分别代表不同的匹配满意程度：
- Extended Hexagon-based Search（六边形模板反复搜索） 满意
- the third step with a small search pattern（小菱形模板反复搜索） 很满意
但是如果在不甚满意的情况下，Early Termination会不作跳转，直接执行下一步
经过上面的整像素mv预测后，得到其中最佳的整像素mv，如果该mv经Early Termination判断为不甚满意，会以该mv为中心，直接开始UMH搜索
1.Unsymmetrical-cross search（非对称十字搜索）
非对称十字搜索会先后对x轴与y轴进行搜索，y轴的搜索范围是x轴的一半，这是因为在一般的视频中，镜头的纵向移动距离会比较短，横向移动距离会比较长，而且比较常见。搜索时，横轴的搜索范围是search range，而纵轴会是它的一般。
2.Spiral search（螺旋搜索）
螺旋搜索采用的是full search（全搜索）的搜索方法，但是搜索步长只有24，相当于5x5的区域。而全搜索会对整个搜索范围进行搜索。
3.Uneven Multi-Hexagon-grid Search（不规律六边形模板搜索）
这种搜索方式是以当前mv指向的像素点为圆心，一圈一圈地往外搜索，一旦在某个圈内搜索到更佳的位置，立刻停止搜索，否则搜索完整个搜索范围
4.Extended Hexagon-based Search（六边形模板反复搜索）
不同于上一个搜索方式，这种搜索方式是以当前最佳mv指向的像素点为圆心，进行一次六边形模板搜索，一旦搜索到某个更佳的位置，则以此位置为圆心，重新进行一次六边形模板搜索。如果没有比圆心更佳的位置，则终止搜索。
5.the third step with a small search pattern（小菱形模板反复搜索）
类似Extended Hexagon-based Search（六边形模板反复搜索）的搜索方式，不过把六边形换成了菱形
以上可参照jvt-G016
JM8.6
/*! ************************************************************************ * \brief用非对称十字形多层次六边形格点搜索算法进行运动搜索 * FastIntegerPelBlockMotionSearch: fast pixel block motion search * this algrithm is called UMHexagonS(see JVT-D016),which includes * four steps with different kinds of search patterns * \par Input: * pel_t** orig_pic, // <-- original picture * int ref, // <-- reference frame (0... or -1 (backward)) * int pic_pix_x, // <-- absolute x-coordinate of regarded AxB block * int pic_pix_y, // <-- absolute y-coordinate of regarded AxB block * int blocktype, // <-- block type (1-16x16 ... 7-4x4) * int pred_mv_x, // <-- motion vector predictor (x) in sub-pel units * int pred_mv_y, // <-- motion vector predictor (y) in sub-pel units * int* mv_x, // --> motion vector (x) - in pel units * int* mv_y, // --> motion vector (y) - in pel units * int search_range, // <-- 1-d search range in pel units * int min_mcost, // <-- minimum motion cost (cost for center or huge value) * double lambda // <-- lagrangian parameter for determining motion cost * \par * Three macro definitions defined in this program: * 1. EARLY_TERMINATION: early termination algrithm, refer to JVT-D016.doc * 2. SEARCH_ONE_PIXEL: search one pixel in search range * 3. SEARCH_ONE_PIXEL1(value_iAbort): search one pixel in search range, * but give a parameter to show if mincost refeshed * \ Main contributors: (see contributors.h for copyright, address and affiliation details) * Zhibo Chen <chenzhibo@tsinghua.org.cn> * JianFeng Xu <fenax@video.mdc.tsinghua.edu.cn> * \date : 2003.8 ************************************************************************ */int // ==> minimum motion cost after searchFastIntegerPelBlockMotionSearch (pel_t** orig_pic, // <-- not used int ref, // <-- reference frame (0... or -1 (backward)) int list, int pic_pix_x, // <-- absolute x-coordinate of regarded AxB block int pic_pix_y, // <-- absolute y-coordinate of regarded AxB block int blocktype, // <-- block type (1-16x16 ... 7-4x4) int pred_mv_x, // <-- motion vector predictor (x) in sub-pel units MV_pred_space 中值预测矢量 int pred_mv_y, // <-- motion vector predictor (y) in sub-pel units int* mv_x, /* --> motion vector (x) - in pel units 按照H.264标准算法进行的运动矢量预测得到MV_pred 指的是SetMotionVectorPreditor函数预测的MV 和中值预测的区别在于SetMotionVectorPreditor函数预测的MV的参考邻块和当前块必须参 考同一个参考帧，而中值预测的邻块则没有这个要求，二者可能一样，也可能不同*/ int* mv_y, // --> motion vector (y) - in pel units int search_range, // <-- 1-d search range in pel units int min_mcost, // <-- minimum motion cost (cost for center or huge value) double lambda) // <-- lagrangian parameter for determining motion cost{ static int Diamond_x[4] = {-1, 0, 1, 0};//对应不同算法 菱形插值 static int Diamond_y[4] = {0, 1, 0, -1}; static int Hexagon_x[6] = {2, 1, -1, -2, -1, 1};//六角形插值 static int Hexagon_y[6] = {0, -2, -2, 0, 2, 2}; static int Big_Hexagon_x[16] = {0,-2, -4,-4,-4, -4, -4, -2, 0, 2, 4, 4, 4, 4, 4, 2}; static int Big_Hexagon_y[16] = {4, 3, 2, 1, 0, -1, -2, -3, -4, -3, -2, -1, 0, 1, 2, 3};//大六角形插值 int pos, cand_x, cand_y, mcost; pel_t *(*get_ref_line)(int, pel_t*, int, int, int, int); int list_offset = ((img->MbaffFrameFlag)&&(img->mb_data[img->current_mb_nr].mb_field))? img->current_mb_nr%2 ? 4 : 2 : 0; pel_t* ref_pic = listX[list+list_offset][ref]->imgY_11;//img->type==B_IMG? Refbuf11 [ref+((mref==mref_fld)) +1] : Refbuf11[ref]; int best_pos = 0; // position with minimum motion cost int max_pos = (2*search_range+1)*(2*search_range+1); // number of search positions int lambda_factor = LAMBDA_FACTOR (lambda); // factor for determining lagragian motion cost int mvshift = 2; // motion vector shift for getting sub-pel units int blocksize_y = input->blc_size[blocktype][1]; // vertical block size int blocksize_x = input->blc_size[blocktype][0]; // horizontal block size int blocksize_x4 = blocksize_x >> 2; // horizontal block size in 4-pel units int pred_x = (pic_pix_x << mvshift) + pred_mv_x; // predicted position x (in sub-pel units) int pred_y = (pic_pix_y << mvshift) + pred_mv_y; // predicted position y (in sub-pel units) int center_x = pic_pix_x + *mv_x; // center position x (in pel units) int center_y = pic_pix_y + *mv_y; // center position y (in pel units) int best_x, best_y; int check_for_00 = (blocktype==1 && !input->rdopt && img->type!=B_SLICE && ref==0); int search_step,iYMinNow, iXMinNow; int i,m, iSADLayer; int iAbort; int N_Bframe = input->successive_Bframe; float betaSec,betaThird; int height=((img->MbaffFrameFlag)&&(img->mb_data[img->current_mb_nr].mb_field))?img->height/2:img->height; //===== set function for getting reference picture lines ===== if ((center_x > search_range) && (center_x < img->width -1-search_range-blocksize_x) && (center_y > search_range) && (center_y < height-1-search_range-blocksize_y) ) { get_ref_line = FastLineX; } else { get_ref_line = UMVLineX; //无运动矢量限制，需像素拓展 } //////allocate memory for search state////////////////////////// //初始化搜索标记 memset(McostState[0],0,(2*search_range+1)*(2*search_range+1)*4); ///////Threshold defined for early termination/////////////////// //为早期终止设定门限值 if(ref>0) { if(pred_SAD_ref!=0) { betaSec = Bsize[blocktype]/(pred_SAD_ref*pred_SAD_ref)-AlphaSec[blocktype]; betaThird = Bsize[blocktype]/(pred_SAD_ref*pred_SAD_ref)-AlphaThird[blocktype]; } else { betaSec = 0; betaThird = 0; } } else { if(blocktype==1) { if(pred_SAD_space !=0) { betaSec = Bsize[blocktype]/(pred_SAD_space*pred_SAD_space)-AlphaSec[blocktype]; betaThird = Bsize[blocktype]/(pred_SAD_space*pred_SAD_space)-AlphaThird[blocktype]; } else { betaSec = 0; betaThird = 0; } } else { if(pred_SAD_uplayer !=0) { betaSec = Bsize[blocktype]/(pred_SAD_uplayer*pred_SAD_uplayer)-AlphaSec[blocktype]; betaThird = Bsize[blocktype]/(pred_SAD_uplayer*pred_SAD_uplayer)-AlphaThird[blocktype]; } else { betaSec = 0; betaThird = 0; } } } /*********检测中值预测矢量**************//*其实就是把得到的mv_pred取整得到的预测矢量*/ // MV_pred_space 中值预测矢量 //check the center median predictor cand_x = center_x ; cand_y = center_y ; mcost = MV_COST (lambda_factor, mvshift, cand_x, cand_y, pred_x, pred_y);//通过计算候选mv所占用的bit得到mv_cost = lambda * bit_of_mv mcost = PartCalMad(ref_pic, orig_pic, get_ref_line,blocksize_y,blocksize_x,blocksize_x4,mcost,min_mcost,cand_x,cand_y);//cost = mv_cost + SAD McostState[search_range][search_range] = mcost; if (mcost < min_mcost) { min_mcost = mcost; best_x = cand_x; best_y = cand_y; } iXMinNow = best_x; iYMinNow = best_y; for (m = 0; m < 4; m++) //小菱形检测 { cand_x = iXMinNow + Diamond_x[m]; cand_y = iYMinNow + Diamond_y[m]; SEARCH_ONE_PIXEL } /*****************原点检测***************************************/ if(center_x != pic_pix_x || center_y != pic_pix_y) { cand_x = pic_pix_x ; cand_y = pic_pix_y ; SEARCH_ONE_PIXEL iXMinNow = best_x; iYMinNow = best_y; for (m = 0; m < 4; m++)//小菱形检测 { cand_x = iXMinNow + Diamond_x[m]; cand_y = iYMinNow + Diamond_y[m]; SEARCH_ONE_PIXEL } } /**********************上层块预测矢量检测*********************************/ if(blocktype>1)// { cand_x = pic_pix_x + (pred_MV_uplayer[0]/4); cand_y = pic_pix_y + (pred_MV_uplayer[1]/4); SEARCH_ONE_PIXEL if ((min_mcost-pred_SAD_uplayer)<pred_SAD_uplayer*betaThird) goto third_step; else if((min_mcost-pred_SAD_uplayer)<pred_SAD_uplayer*betaSec) goto sec_step; } /****************相应块预测***************************************/ //coordinate position prediction if ((img->number > 1 + ref && ref!=-1) || (list == 1 && (Bframe_ctr%N_Bframe) > 1)) //for debug { cand_x = pic_pix_x + pred_MV_time[0]/4; cand_y = pic_pix_y + pred_MV_time[1]/4; SEARCH_ONE_PIXEL } /******************相邻参考帧预测*********************************/ //prediciton using mV of last ref moiton vector if (input->PicInterlace == FIELD_CODING)//场编码，用最近的场MV预测 { if ((list==0 && ref > 0) || (img->type == B_SLICE && list == 0 && (ref==0 ||ref==2 ) )) //Notes: for interlace case, ref==1 should be added { cand_x = pic_pix_x + pred_MV_ref[0]/4; cand_y = pic_pix_y + pred_MV_ref[1]/4; SEARCH_ONE_PIXEL } } else { //多参考帧预测时，用另一帧的MV预测 if ((list==0 && ref > 0) || (img->type == B_SLICE && list == 0 && ref==0 )) //Notes: for interlace case, ref==1 should be added { cand_x = pic_pix_x + pred_MV_ref[0]/4; cand_y = pic_pix_y + pred_MV_ref[1]/4; SEARCH_ONE_PIXEL } } //small local search iXMinNow = best_x; iYMinNow = best_y; for (m = 0; m < 4; m++)//小菱形搜索 { cand_x = iXMinNow + Diamond_x[m]; cand_y = iYMinNow + Diamond_y[m]; SEARCH_ONE_PIXEL } //early termination algrithm, refer to JVT-D016 //根据SAD值判断需要跳转的步骤，SAD较小时转到步骤3，较大时转到步骤2，很大时转到步骤1 EARLY_TERMINATION if(blocktype>6) goto sec_step; else goto first_step; first_step: //Unsymmetrical-cross search 不甚满意 iXMinNow = best_x; iYMinNow = best_y; for(i=1;i<=search_range/2;i++)//水平方向搜索 { search_step = 2*i - 1; cand_x = iXMinNow + search_step; cand_y = iYMinNow ; SEARCH_ONE_PIXEL cand_x = iXMinNow - search_step; cand_y = iYMinNow ; SEARCH_ONE_PIXEL } //垂直方向搜索，注意垂直方向搜索点比水平方向少，考虑到了水平方向较垂直方向重要 for(i=1;i<=search_range/4;i++) { search_step = 2*i - 1; cand_x = iXMinNow ; cand_y = iYMinNow + search_step; SEARCH_ONE_PIXEL cand_x = iXMinNow ; cand_y = iYMinNow - search_step; SEARCH_ONE_PIXEL } //early termination algrithm, refer to JVT-D016 //在这里也进行中止、跳转检测，考虑到一般序列中含有大量水平、垂直方向的运动。 EARLY_TERMINATION iXMinNow = best_x; iYMinNow = best_y; //螺旋搜索，类似全搜索法，只搜索前25点，相当于5×5区域全搜索 for(pos=1;pos<25;pos++) { cand_x = iXMinNow + spiral_search_x[pos]; cand_y = iYMinNow + spiral_search_y[pos]; SEARCH_ONE_PIXEL } //early termination algrithm, refer to JVT-D016 EARLY_TERMINATION // Uneven Multi-Hexagon-grid Search //超六边形模板搜索，（多圈） for(i=1;i<=search_range/4; i++) { iAbort = 0; for (m = 0; m < 16; m++) { cand_x = iXMinNow + Big_Hexagon_x[m]*i; cand_y = iYMinNow + Big_Hexagon_y[m]*i; SEARCH_ONE_PIXEL1(1) } if (iAbort) { //early termination algrithm, refer to JVT-D016 EARLY_TERMINATION } }// 六边形模板反复搜索（也可以用大菱形代替），搜索完后进入第三步骤sec_step: //Extended Hexagon-based Search 满意 iXMinNow = best_x; iYMinNow = best_y; for(i=0;i<search_range;i++) { iAbort = 1; for (m = 0; m < 6; m++) { cand_x = iXMinNow + Hexagon_x[m]; cand_y = iYMinNow + Hexagon_y[m]; SEARCH_ONE_PIXEL1(0) } if(iAbort) break; iXMinNow = best_x; iYMinNow = best_y; }// 小菱形模板反复搜索，得到最终的运动矢量 third_step: // the third step with a small search pattern 很满意 iXMinNow = best_x; iYMinNow = best_y; for(i=0;i<search_range;i++) { iSADLayer = 65536; iAbort = 1; for (m = 0; m < 4; m++) { cand_x = iXMinNow + Diamond_x[m]; cand_y = iYMinNow + Diamond_y[m]; SEARCH_ONE_PIXEL1(0) } if(iAbort) break; iXMinNow = best_x; iYMinNow = best_y; } *mv_x = best_x - pic_pix_x; *mv_y = best_y - pic_pix_y; return min_mcost; }
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